Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds meaningful behavioral context beyond the annotations: it may call AI, requires authentication/entitlement, counts toward quotas, and tells the agent to review the result. These details are not present in the annotation block and are valuable for a non-read-only, non-idempotent tool. It does not contradict annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences and economical. It front-loads the core behavior, then adds operational constraints, then the sibling distinction. No sentence is wasted, though the ordering of 'review the result' before the auth note is slightly arbitrary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers authentication, quota impact, and the need to review output, which is helpful. However, given the tool has multiple task modes, no output schema, and no per-task behavior details, an agent cannot fully anticipate what will happen for tasks like 'retrieve', 'negotiate', or 'compliance_check'. It is adequate but has clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, but it only weakly references the parameters: 'supplied text' points to 'input' and 'selected task' points to 'task'. It does not explain the task enum variants, what each task expects, or the expected format of input. This is a significant gap for a tool with zero schema-level parameter descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear action ('Process supplied text') and result ('may call AI and return generated content'), giving the tool an identifiable purpose as an AI text-generation utility. It also differentiates from the sibling lookup_words by explicitly saying that one is for stored lexical records only. It is not a perfect 5 because 'Process' is somewhat generic and the range of tasks is only implied.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives practical usage context: it requires a Word Orb key, counts toward quotas, and may call AI. It also provides one explicit exclusion ('Use lookup_words for stored lexical records only'), which helps an agent avoid the closest sibling. It does not exhaustively cover when to prefer other siblings like translate_word or define_term, but the guidance is sufficient for basic routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.